Field
The present application relates generally to biological rhythm disorders. More specifically, the present application is directed to a system and method to select signal segments for analysis of a biological rhythm disorder (e.g., heart rhythm disorder).
Brief Discussion of Related Art
Biological rhythm disorders, such as heart (cardiac) rhythm disorders, are common and represent significant causes of morbidity and death throughout the world. Malfunction of the electrical system in the heart represents a proximate cause of the heart rhythm disorders. Heart rhythm disorders exist in many forms, of which the most complex and difficult to treat are atrial fibrillation (AF), ventricular tachycardia (VT) and ventricular fibrillation (VF). Other rhythm disorders are more simple to treat, but may also be clinically significant including atrial tachycardia (AT), supraventricular tachycardia (SVT), atrial flutter (AFL), supraventricular ectopic complexes/beats (SVE) and premature ventricular complexes/beats (PVC).
Previously, treatment of heart rhythm disorders—particularly complex rhythm disorders of AF, VF and polymorphic VT—has been difficult because the location in the heart that harbors the source of the heart rhythm disorder could not be identified. There have been various theories of how complex rhythm disorders function and clinical applications for treating these complex rhythm disorders. However, none of the applications proved fruitful in the treatment of complex rhythm disorders.
Recently, there has been a breakthrough discovery that for the first time identified sources associated with complex heart rhythm disorders. This technological breakthrough successfully analyzed and reconstructed cardiac activation information (activation onset times) in signals obtained from electrodes of catheters introduced into the patient's heart to identify rotational activation patterns (rotational sources such as rotors), as well as focal sources, which cause and sustain a large percentage of the heart rhythm disorders worldwide. Treatment of the heart rhythm disorders can thus be targeted to the rotational and/or focal sources in the patient's heart to eliminate the heart rhythm disorders. Such treatment can be successfully delivered by ablation, for example.
As aforementioned, cardiac signals are generally obtained (e.g. sensed, acquired, or recorded) from electrodes of catheters introduced into the patient's heart. Many sources of noise are often embedded or superimposed in the signals when the signals are obtained from the patient. These sources can include electrical activity from another part of the patient's heart, other anatomic structures of the patient, motion artifacts from movement of the electrodes and/or movement of the patient (e.g., breathing), mechanical cross-talk resulting from electrodes contacting each other, saturation of electronic amplifiers, radio frequency (RF) energy from external systems, as well as other sources of noise. In addition, the electrodes can have various levels of contact (or non-contact) with the patient's heart that can reduce the amplitude of the signals and, in the worst cases, can even result in the absence of electrical activity in the signals.
Reconstruction of the cardiac activation information (activation onset times) requires analyses of the signals that can be computationally-intensive as well as time-intensive. It may not be advantageous due to these or other computational constraints to analyze the entirety of the signals. Moreover, certain portions of these signals—in some cases, extensive portions—can be affected by noise. In such circumstances, it is may be advantageous to avoid portions the signals where analysis is complex and limited by noise superimposed in the signals.
Analysis of the entirety of these signals can affect negatively the time and accuracy in identifying a source of a heart rhythm disorder, as well as the accuracy in targeting of the source of the heart rhythm disorder for treatment and elimination.
Accordingly, it is desirable to identify portions of these signals (e.g., signal segments) that include periodic cardiac information with the reduced amount of noise for further analysis, which can improve the time and accuracy in identifying the source of a heart rhythm disorder, as well as the time and accuracy in the targeting of the source of the heart rhythm disorder for treatment and elimination.